Sang Choe

Current: PhD, Carnegie Mellon University
E-mail: sangkeuc [at]
Office: GHC 5511

LinkedIn | Google Scholar | GitHub | Twitter


I am Sang Choe, a third-year CS PhD student in Language Technologies Institute at Carnegie Mellon University, advised by Eric Xing.

My research aims to make AI programming easier for all developers, ranging from academic researchers to industry practitioners. Towards this goal, I work on designing a high-level AI programming framework that abstracts away low-level programming details and improves automation and reusability, while minimizing abstraction penalty such as flexibilty and efficiency. Observing that the advancement in programming frameworks in traditional software technologies (e.g. TypeScript, Django) has significantly accelerated their adoption, I believe we will see the similar trend in AI soon, hopefully led by my research!

In technical terms, my research lies in the intersection of:

◆  systems for machine learning
◆  programming models for machine learning
◆  automated machine learning
◆  data-centric AI

Previously, I completed MS in Language Technologies at Carnegie Mellon University under the guidance of Jaime Carbonell. Before that, I earned BS in Electrical Computer Engineering & Mathematics (double major) from Seoul National University. I had also spent time as a research intern at Microsoft in 2021.


◆  Betty got accepted as an oral presentation at ICLR 2023!
◆  Released Betty, a PyTorch library for easy, scalable, and modular meta-learning!
◆  Received CMU Presidential Scholarship for PhD!
◆  Started research internship at Microsoft in Summer 2021!
◆  Won Jay Lepreau Best Paper Award in OSDI 2021!

Betty: An Automatic Differentiation Library for Multilevel Optimization [code] ICLR, 2023
Sang Keun Choe, Willie Neiswanger, Pengtao Xie, and Eric Xing
Oral (1.8% acceptance rate)

Pollux: Co-adaptive Cluster Scheduling for Goodput-Optimized Deep Learning [code] OSDI, 2021
Aurick Qiao, Sang Keun Choe, Suhas Subramanya, Willie Neiswanger, Qirong Ho, Hao Zhang, Greg Ganger, Eric Xing
🏆 Jay Lepreau Best Paper Award

On Orthogonal Jacobian Regularization in Deep Neural Networks SEDL Workshop @ NeurIPS, 2019
Sang Keun Choe*, Hosan Jeong*, Jaime Carbonell

On Leveraging the Visual Modality for Neural Machine Translation INLG, 2019
Vikas Raunak*, Sang Keun Choe*, Quanyang Lu*, Yi Xu*, Florian Metze

Audio Cover Song Identification using Convolutional Neural Network ICASSP, 2017
Sungkyung Chang, Juheon Lee, Sang Keun Choe, Kyogu Lee


CMU Presidential Scholarship, Carnegie Mellon University
Jay Lepreau Best Paper Award, OSDI
Kwanjeong Scholarship for Graduate Study, Kwanjeong Educational Foundation
Best Undergraduate Engineering Student Award, Seoul National University
Presidential Scholarship for Science and Engineering Study, Korea Student Aid Foundation
Gold Medal, Korea Collegiate Mathematical Competition
Silver Medal, Korea Mathematical Olympiad

In my spare time, I serve as a dog walker for my three-year-old bernedoodle, Betty.

© Copyright 2023 Sang Choe. Powered by Jekyll with minimal theme. Last updated in Feb 2023.